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利用混合模型对核心家庭数量性状基因座进行连锁和关联研究。

Linkage and association studies of QTL for nuclear families by mixed models.

作者信息

Fan Ruzong, Xiong Momiao

机构信息

Department of Statistics, Texas A&M University, 447 Blocker Building, College Station, TX 77843-3143, USA.

出版信息

Biostatistics. 2003 Jan;4(1):75-95. doi: 10.1093/biostatistics/4.1.75.

Abstract

The transmission disequilibrium test (TDT) has been utilized to test the linkage and association between a genetic trait locus and a marker. Spielman et al. (1993) introduced TDT to test linkage between a qualitative trait and a marker in the presence of association. In the presence of linkage, TDT can be applied to test for association for fine mapping (Martin et al., 1997; Spielman and Ewens, 1996). In recent years, extensive research has been carried out on the TDT between a quantitative trait and a marker locus (Allison, 1997; Fan et al., 2002; George et al., 1999; Rabinowitz, 1997; Xiong et al., 1998; Zhu and Elston, 2000, 2001). The original TDT for both qualitative and quantitative traits requires unrelated offspring of heterozygous parents for analysis, and much research has been carried out to extend it to fit for different settings. For nuclear families with multiple offspring, one approach is to treat each child independently for analysis. Obviously, this may not be a valid method since offspring of one family are related to each other. Another approach is to select one offspring randomly from each family for analysis. However, with this method much information may be lost. Martin et al. (1997, 2000) constructed useful statistical tests to analyse the data for qualitative traits. In this paper, we propose to use mixed models to analyse sample data of nuclear families with multiple offspring for quantitative traits according to the models in Amos (1994). The method uses data of all offspring by taking into account their trait mean and variance-covariance structures, which contain all the effects of major gene locus, polygenic loci and environment. A test statistic based on mixed models is shown to be more powerful than the test statistic proposed by George et al. (1999) under moderate disequilibrium for nuclear families. Moreover, it has higher power than the TDT statistic which is constructed by randomly choosing a single offspring from each nuclear family.

摘要

传递不平衡检验(TDT)已被用于检测遗传性状位点与标记之间的连锁和关联。斯皮尔曼等人(1993年)引入TDT来检测定性性状与标记在存在关联情况下的连锁。在存在连锁的情况下,TDT可用于检测关联以进行精细定位(马丁等人,1997年;斯皮尔曼和埃文斯,1996年)。近年来,针对数量性状与标记位点之间的TDT开展了广泛研究(艾利森,1997年;范等人,2002年;乔治等人,1999年;拉比诺维茨,1997年;熊等人,1998年;朱和埃尔斯顿,2000年、2001年)。针对定性和数量性状的原始TDT都需要杂合子父母的无关后代进行分析,并且已经开展了大量研究来对其进行扩展以适用于不同情况。对于有多个后代的核心家庭,一种方法是将每个孩子独立对待进行分析。显然,这可能不是一种有效的方法,因为一个家庭的后代彼此相关。另一种方法是从每个家庭中随机选择一个后代进行分析。然而,使用这种方法可能会丢失很多信息。马丁等人(1997年、2000年)构建了有用的统计检验来分析定性性状的数据。在本文中,我们建议根据阿莫斯(1994年)的模型,使用混合模型来分析有多个后代的核心家庭的数量性状样本数据。该方法通过考虑所有后代的性状均值和方差协方差结构来使用所有后代的数据,这些结构包含主基因位点、多基因位点和环境的所有效应。结果表明,在中等不平衡情况下,基于混合模型的检验统计量比乔治等人(1999年)提出的检验统计量对核心家庭更具效力。此外,它比通过从每个核心家庭中随机选择一个后代构建的TDT统计量具有更高的效力。

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